Repository: predictionio-site
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http://git-wip-us.apache.org/repos/asf/predictionio-site/blob/c17b9607/tryit/index.html
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-<!DOCTYPE html><html><head><title>Try PredictionIO</title><meta 
charset="utf-8"/><meta content="IE=edge,chrome=1" 
http-equiv="X-UA-Compatible"/><meta name="viewport" 
content="width=device-width, initial-scale=1.0"/><meta class="swiftype" 
name="title" data-type="string" content="Try PredictionIO"/><link 
rel="canonical" href="https://predictionio.apache.org/tryit/"/><link 
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true });}catch(e){}</script></head><body class="tryit"><div 
id="global"><header><div class="container" id="header-wrapper"><div 
class="row"><div class="col-sm-12"><div id="logo-wrapper"><span 
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href="http://predictionio.apache.org/";><img alt="Apache PredictionIO" id="logo" 
src="/images/logos/logo-ee2b9bb3.png"/></a><span>®</span></div><div 
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id="page" class="container"><main id="main" role="main" 
data-swiftype-index="true"><div id="content"><div class="codepicnic"><div 
class="tutorial"><div class="j
 carousel-wrapper"><ul class="jcarousel-pagination"></ul><div 
class="jcarousel"><ul><li><h2>Introduction</h2><p>To see how PredictionIO 
works, you can follow this quick tutorial to:</p><p>Start the PredictionIO 
server</p><p>Build, train, and deploy a predictive model with pre-imported 
data.</p><p>Query prediction results.</p><p><a class="button-primary" 
id="tryit-start" href="#">Start</a></p></li><li><h2>Start</h2><p>Start 
PredictionIO and it's dependancies with:</p><p><code>$ 
pio-start-all</code></p><h2>Check Status</h2><p>At any time you can 
run:</p><p><code>$ pio status</code></p><p>Which checks the status of 
PredictionIO and it's dependancies.</p></li><li><h2>Build</h2><p>All engine 
commands need to be run from within the engine directory:</p><p><code>$ cd 
~/PredictionIO/MyEngine</code></p><p>Build the engine with:</p><p><code>$ pio 
build</code></p></li><li><h2>Train and Deploy</h2><h3>Train the 
engine</h3><p><a href="http://grouplens.org/datasets/movielens/";>Sample 
data</a> is a
 lready imported, you can train the model the data by running:</p><p><code>$ 
pio train</code></p><h3>Deploy the trained engine</h3><p>Deploy the trained 
engine as a background process:</p><p><code>$ pio deploy 
&</code></p></li><li><h2>Querying Results</h2><p>You can query results using 
cURL with after you see "Ready to serve":</p><p><code>$ curl -H "Content-Type: 
application/json" -d '{ "items": ["296"], "num": 5 }' 
http://localhost:8000/queries.json</code></p><p>This will return 5 recomended 
movies for movie 296 (Pulp Fiction).</p></li><li><h2>Next Steps</h2><p><a 
href="http://predictionio.apache.org/install/";>Install</a> PredictionIO on your 
own computer!</p><h3>Support</h3><p>Get support on our <a 
href="https://groups.google.com/forum/#!forum/predictionio-user";>Google 
Group</a> or on Twitter <a 
href="https://twitter.com/predictionio/";>@PredictionIO</a></p></li></ul><div 
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data-swiftype-index="true"><div id="content"><div class="codepicnic"><div 
class="tutorial"><div class="j
 carousel-wrapper"><ul class="jcarousel-pagination"></ul><div 
class="jcarousel"><ul><li><h2>Introduction</h2><p>To see how PredictionIO 
works, you can follow this quick tutorial to:</p><p>Start the PredictionIO 
server</p><p>Build, train, and deploy a predictive model with pre-imported 
data.</p><p>Query prediction results.</p><p><a class="button-primary" 
id="tryit-start" href="#">Start</a></p></li><li><h2>Start</h2><p>Start 
PredictionIO and it's dependencies with:</p><p><code>$ 
pio-start-all</code></p><h2>Check Status</h2><p>At any time you can 
run:</p><p><code>$ pio status</code></p><p>Which checks the status of 
PredictionIO and it's dependencies.</p></li><li><h2>Build</h2><p>All engine 
commands need to be run from within the engine directory:</p><p><code>$ cd 
~/PredictionIO/MyEngine</code></p><p>Build the engine with:</p><p><code>$ pio 
build</code></p></li><li><h2>Train and Deploy</h2><h3>Train the 
engine</h3><p><a href="http://grouplens.org/datasets/movielens/";>Sample 
data</a> is a
 lready imported, you can train the model the data by running:</p><p><code>$ 
pio train</code></p><h3>Deploy the trained engine</h3><p>Deploy the trained 
engine as a background process:</p><p><code>$ pio deploy 
&</code></p></li><li><h2>Querying Results</h2><p>You can query results using 
cURL with after you see "Ready to serve":</p><p><code>$ curl -H "Content-Type: 
application/json" -d '{ "items": ["296"], "num": 5 }' 
http://localhost:8000/queries.json</code></p><p>This will return 5 recommended 
movies for movie 296 (Pulp Fiction).</p></li><li><h2>Next Steps</h2><p><a 
href="http://predictionio.apache.org/install/";>Install</a> PredictionIO on your 
own computer!</p><h3>Support</h3><p>Get support on our <a 
href="https://groups.google.com/forum/#!forum/predictionio-user";>Google 
Group</a> or on Twitter <a 
href="https://twitter.com/predictionio/";>@PredictionIO</a></p></li></ul><div 
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